Triple
T2119388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English First Division 1955–56 |
E43882
|
entity |
| Predicate | topScorer |
P6605
|
FINISHED |
| Object |
Nat Lofthouse
Nat Lofthouse was a legendary English centre-forward for Bolton Wanderers and England, renowned for his powerful, fearless playing style in the 1940s and 1950s.
|
E234086
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Nat Lofthouse | Statement: [English First Division 1955–56, topScorer, Nat Lofthouse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nat Lofthouse Context triple: [English First Division 1955–56, topScorer, Nat Lofthouse]
-
A.
Bill Peet
Bill Peet was an American children’s book author and longtime Disney story artist known for his influential work on many classic animated films.
-
B.
Thomas Lownds
Thomas Lownds was an 18th-century London publisher best known for issuing the first edition of Horace Walpole’s pioneering Gothic novel "The Castle of Otranto."
-
C.
Art Eggleton
Art Eggleton is a Canadian politician who served as a long-time mayor of Toronto before later holding federal cabinet and Senate roles.
-
D.
Jack Kitchin
Jack Kitchin was a film editor known for his work on early Hollywood productions, including classic musicals of the 1930s.
-
E.
Richard Towers
Richard Towers is a cinematographer known for his work on the film "Doctor X."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nat Lofthouse Triple: [English First Division 1955–56, topScorer, Nat Lofthouse]
Generated description
Nat Lofthouse was a legendary English centre-forward for Bolton Wanderers and England, renowned for his powerful, fearless playing style in the 1940s and 1950s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nat Lofthouse Target entity description: Nat Lofthouse was a legendary English centre-forward for Bolton Wanderers and England, renowned for his powerful, fearless playing style in the 1940s and 1950s.
-
A.
Bill Peet
Bill Peet was an American children’s book author and longtime Disney story artist known for his influential work on many classic animated films.
-
B.
Thomas Lownds
Thomas Lownds was an 18th-century London publisher best known for issuing the first edition of Horace Walpole’s pioneering Gothic novel "The Castle of Otranto."
-
C.
Art Eggleton
Art Eggleton is a Canadian politician who served as a long-time mayor of Toronto before later holding federal cabinet and Senate roles.
-
D.
Jack Kitchin
Jack Kitchin was a film editor known for his work on early Hollywood productions, including classic musicals of the 1930s.
-
E.
Richard Towers
Richard Towers is a cinematographer known for his work on the film "Doctor X."
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb32efb48190bcb99f30787a3a55 |
completed | March 7, 2026, 5:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae307b08148190aa201ac038ce9944 |
completed | March 9, 2026, 2:29 a.m. |
| NEDg | Description generation | batch_69ae3106488c8190a044d843a10f531a |
completed | March 9, 2026, 2:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae31889bc0819092810ade1961d10e |
completed | March 9, 2026, 2:33 a.m. |
Created at: March 4, 2026, 7:44 p.m.